QA Engineer

Friendli Suite is our SaaS platform that includes microservices, a frontend, multi-cloud infrastructure, enterprise authentication, billing, and organization management. However, what makes this role unique is that our platform delivers AI inference. Validating whether inference works well is a problem that traditional QA methods do not fully solve. A deployment can succeed technically and still produce poor inference.

We are looking for a dedicated QA engineer who can own the product's quality, ensuring our product works the way any well-run SaaS platform should, while also developing the approaches needed to validate AI inference quality, model deployments, and integrations that traditional testing alone cannot cover.

• Own quality across FriendliAI's full platform stack: backend microservices, frontend, model deployments, and inference pipelines.

• Build and maintain automated test suites using pytest, covering unit, integration, and regression testing across backend services.

• Develop and run load and scalability tests using Locust to validate platform performance under real-world conditions.

• Own frontend and end-to-end testing with Playwright across the full user-facing product.

• Design and implement test strategies that account for LLM inference.

• Work closely with infrastructure and backend engineers to validate model deployment workflows, multi-cloud orchestration, and service integrations.

• Identify coverage gaps, prioritize test investment, and build tooling and pipelines.

• 3+ years of experience in software quality engineering, with a track record of owning test strategy.

• Bachelor's or Master's degree in Computer Science, Computer Engineering, or equivalent.

• Proficiency in Python and hands-on experience with pytest for test automation.

• Experience with load and performance testing tools such as Locust.

• Experience with browser automation and end-to-end testing frameworks such as Playwright.

• Working knowledge of LLM serving.

• Strong experience testing distributed systems with multiple interconnected components.

• Strong systems thinking.

• Comfortable working in a fast-moving environment.

• Familiarity with AI infrastructure or model serving systems

• Experience building QA infrastructure from scratch in an early-stage or scaling environment.

• Background in performance and scalability testing for cloud-native or multi-cloud systems.

• Experience covering both backend and frontend testing in a single role.

• Exposure to observability tooling and how it supports debugging and quality validation.

• Flexible working hours

• Daily lunch and dinner provided; unlimited snacks and beverages

• Supportive and highly collaborative work environment

• Health check-up support and top-tier equipment/hardware support

• A front-row seat to the generative AI infrastructure revolution

• Competitive compensation, startup equity, health insurance, and other benefits.

FriendliAI is building the world’s best AI inference platform that makes large language and multi-modal models fast, efficient, and deployable at scale. We power high-throughput, low-latency AI workloads for organizations worldwide and integrate directly with Hugging Face, giving developers instant access to over 500,000 open-source models.

We are a small, fast-moving team doing work that matters at one of the most exciting moments in the history of technology. With our world-class inference engine, we are building a platform that the AI industry can actually rely on.